class_docstr: Abstract class for Flavor Backend.
  This class defines the API interface for local model deployment of MLflow model flavors.
docstr: Performs any preparation necessary to predict or serve the model, for example
  downloading dependencies or initializing a conda environment. After preparation,
  calling predict or serve should be fast.
docstr_tok: ["Performs","any","preparation","necessary","to","predict","or","serve","the","model",",","for","example","downloading","dependencies","or","initializing","a","conda","environment",".","After","preparation",",","calling","predict","or","serve","should","be","fast","."]
code: def prepare_env(self, model_uri, capture_output=False):
      """
      Performs any preparation necessary to predict or serve the model, for example
      downloading dependencies or initializing a conda environment. After preparation,
      calling predict or serve should be fast.
      """
      pass
  
file_path: mlflow/mlflow/models/flavor_backend.py
imports: from abc import ABCMeta, abstractmethod
  from mlflow.utils.annotations import developer_stable
label_desc: Use image node_id 4 for calling the FlavorBackend obj's underlying member method code with example usage: obj.prepare_env(model_uri, capture_output) without return types